Big Data and computational research methods: Opportunities and challenges for cultural industries research

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1 Big Data and computational research methods: Opportunities and challenges for cultural industries research Queensland University of Technology

2 Patrik Wikström Associate Professor Principal Research Fellow, QUT DMRC Research interests 1. Business innovation and digital disruption in the creative and cultural economy 2. Use and development of computational research methods Digital creative economy; Music; Computational social science; Time

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4 QUT QUT DMRC conducts world-leading research that helps society understand and adapt to the social, cultural and economic transformations associated with digital media technologies. Journalism, Public Communication & Democracy Industries, Policies & Economies DIGITAL MEDIA Digital Method Innovation Technologies & Practices in Everyday Life

5 Agenda The computational turn, Big data Four examples Some methodological considerations Building theory about complex and dynamic phenomena

6 Computational turn (Berry) What has changed? 1. Abundance of data on human behaviour created by the digital traces of our everyday online activities 2. Digital-born methods and tools for largescale data analysis and visualisation

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8 Social networks Examples gg Structural dynamics (Inter)-network information flows Platforms Online user behaviour Multisided market dynamics Sentiment dynamics

9 1. Visit logs 2. Web APIs 3. Web scraping 4. Web archives Examples (different data sources)

10 Clickstream data from visit logs

11 About the study The role of the website in a magazine business Exploratory vs goal-oriented user behaviour

12 Identification of typical user behaviours using hierarchical cluster analysis Page #1 Page #2 Page #3 Page #4

13 Web APIs

14 Public communication via social media platforms

15 The Sydney Siege (Dec 2014) Axel Bruns

16 The Australian Twittersphere Horse Racing ~140k Australian accounts with degree > 1000, as of Sep Hard Right Leftists Football Politics Education AFL TalkbackCycling Agriculture Journalists Literature V8s TV News Adelaide / SA Arts Beer Netizens UFC Media Music Pop Teen Idols Fashion Advertising Food NRL Celebrities Cinema Urban Media Utilities Wine Cricket NRU Cody Simpson Beauty Marketing Hillsong Business Mums PR HR / Support Parenting Real Estate Investing Followback Home Business Sole Traders Self-Help Perth Axel Bruns

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18 Web API Application Programming Interface

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20 Web scraping

21 Web scraping Because many online services do not offer a programming interface to access their data

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23 Example: Changing patterns in the production and consumption of cultural artefacts Data collection Cultural artefacts, Popular music, Artists, albums & tracks Data analytics E.g. Time based, Geographic, Acoustic metadata

24 Changing audio attributes over time: 2 Duration AU UK US

25 Danceability AU UK US

26 Speechiness AU UK US

27 3.5 Acousticness AU UK US

28 Energy AU UK US

29 3 Liveness AU UK US 2 3 4

30 2.5 Loudness AU UK US

31 2 What is this? Is it a measure of music innovation? Is it cyclical? US

32 Beautiful Soup

33 Beautiful Soup

34 Web archives

35 A Battle for Legitimacy

36 A Battle for Legitimacy (sentiment analysis: multiple aspect rating data source: web archive)

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40 Beautiful Soup

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42 Opportunities and challenges Cost efficient Unobtrusive Requires some technical skills Data seduction Apophenia

43 Methodological considerations Qualitative or quantitative data? Are these methods a complement or substitute to traditional methods? E.g. what about motivational drivers? Production v collection of data Raw data is an oxymoron (Gitelman 2013) Ethical concerns? E.g. access often necessitates engagement Is this the end of theory?

44 What is theory? Theory is the answer to queries of why. Theory is about connections among phenomena, a story about why acts, events, structure and thoughts occur. What theory is not // Sutton & Straw, 1995: 378

45 Big data certainly doesn t mean the end of theory (Auerbach, 2014) We no longer need to speculate and hypothesise; we simply need to let machines lead us to the patterns, trends, and relationships in social, economic, political, and environmental relationships. (Graham, 2012) Research Centre

46 Perhaps we need a new approach to theory development?

47 Complex and dynamic phenomena Large number of (locally) interacting elements. Any element is affected by and affects several other elements. The interactions are non-linear: small changes in can cause large effects. They are dynamic and have a history. They evolve and their past is co-responsible for their present behaviour. Often difficult or impossible to define system boundaries. Systems are often far from equilibrium. Micro level actions generate macro level patterns (e.g. Miller & Page 2007)

48 It is challenging to build theory that is able to capture such complexities

49 Traditional modelling approaches are simply not very useful: Verbal models The paper with the largest circulation in a market has financial and economic advantages that enable it to increase advertising and circulation sales by attracting customers from the smaller paper. As the leading paper attracts more circulation, it attracts more advertising, which in turn attracts more circulation, trapping the secondary paper in a circulation spiral that ultimately leads to its demise.

50 Traditional modelling approaches are simply not very useful: Verbal models Signifier sound image Signified concept

51 Traditional modelling approaches are simply not very useful: Statistical (e.g. regression) models

52 Traditional modelling approaches are simply not very useful: Mathematical models Interactions between feral cats, foxes, native carnivores, and rabbits in Australia. System of differential equations

53 Computational modelling, however, is a promising approach Concepts, assumptions, logics represented by a computer program. Allows simulation of model behaviour over time.

54 Computational modelling (e.g. agent-based modelling) may be a way forward

55 Conclusions Data abundance and computational methods enable facilitate cultural and creative industries research from new perspectives. A complement (not a substitute) to traditional methods. We need new approaches to develop theory about these complex and dynamic phenomena. Coding is gradually becoming an essential research skill.

56 Queensland University of Technology Visit! Collaborate!